1. Field of the Invention
The present invention relates to a technique for reducing noise in a captured video.
2. Description of the Related Art
In the field of X-ray video imaging, a two-dimensional digital X-ray radioscopy device has been proposed, in which an inputted X-ray is converted into visible light using a scintillator (a fluorophore) and an image intensifier, and an image of the resulting visible light is captured by a TV camera using a CCD-type image sensor.
Meanwhile, a system that replaces the TV camera with a flat-panel detector has recently been proposed (for example, see Japanese Patent Laid-Open No. 2005-003444).
With the above-mentioned X-ray radioscopy device, it is common to perform various types of image processing in order to improve the quality of the captured video. Noise reduction processing for reducing quantization noise, system noise, and the like is one type of such processing. Recursive filtering is an example of a conventionally-used noise reduction processing (see Japanese Patent Laid-Open No. 2002-112992). As illustrated in FIG. 7, a general recursive filter uses a frame memory 701, which stores one frame's worth of image data; an adder 702 performs weighted adding on the image data of the present frame and the image data of the previous, recursively filtered frame. Temporally random noise is thereby reduced. Expressing this kind of recursive filtering as a mathematical formula results in the following:Yt=(1−a)×Xt+a×Yt-1  (1)
Here, t>0, and Y0=X1.
Here, Xt is image data of the tth frame; Yt is image data of the recursively filtered tth frame; and a is a feedback coefficient. The range of the coefficient a is set to 0<a<1.
As shown by formula (1), with recursive filtering, it is possible to adjust the addition ratio of the image data of the recursively filtered previous frame and the image data of the present frame based on the feedback coefficient. A greater feedback coefficient value results in greater effects on the part of the noise reduction processing.
With the above-mentioned recursive filtering, effect of afterimage appears as motion blur in images that have movement. There is, therefore, a method that detects movement between the present frame and the previous frame based on the difference between the two, and alters the feedback coefficient in each frame in accordance with the detected movement (i.e., reduces the feedback coefficient when the movement is great), when a high value has been set for the feedback coefficient. See, for example, Japanese Patent Laid-Open No. 2005-003444 and Japanese Patent Laid-Open No. 2002-112992.
However, with the abovementioned recursive filtering, when recording is first commenced, no frame exists prior to the first frame, and thus noise suppression cannot be carried out. Furthermore, there is a problem that the noise suppression effect increases as the feedback coefficient is greater, and thus the noise suppression effect varies from frame to frame. For example, if the feedback coefficient is set to 0.8, the noise damping rate (a value obtained by dividing the noise standard deviation in the output image by the noise standard deviation in the input image) decreases as t increases, and the noise damping rate converges when t=∞, as can be seen in FIG. 8.
Further still, with the method that reduces the feedback coefficient as movement increases, the feedback coefficient differs from frame to frame, in accordance with the movement. Therefore, while motion blur can be suppressed, there is a problem in that the noise suppression effects are even more varied than as with formula (1) (the noise suppression effect decreases when movement is great).